Major depressive disorder (MDD) is a common condition that afflicts the general population across a broad spectrum of ages and social backgrounds. The inflammatory hypothesis of depression posits that immune hyperactivation and dysregulated cytokine production are involved in depression. To investigate cytokine profiles in patients with MDD, we examined the levels of the pro-inflammatory cytokines interleukin (IL)-1β, IL-6, IL-8, and tumor necrosis factor (TNF)-α, and those of the anti-inflammatory cytokines IL-10 and transforming growth factor (TGF)-β1 in antidepressant drug-naïve patients with MDD. Compared to healthy controls, patients with MDD had significantly higher levels of IL-1β, IL-10, and TNF-α, but significantly lower levels of IL-8. There were no significant differences in the levels of IL-6 or TGF-β1. We found linear correlations between IL-1β, TNF-α, and IL-8, and the severity of depression, as well as between IL-8 and anxiety level in patients with comorbid anxiety disorder. In addition, higher IL-1β and TNF-α levels were associated with higher Hamilton Depression Rating Scale (HAMD) scores, while higher IL-8 levels were associated with lower HAMD and Hamilton Anxiety Rating Scale scores. Here we present evidence of changes in cytokine levels in antidepressant drug-naïve patients with MDD. Abnormal expression of inflammatory cytokines in patients with depression suggests that depression activates an inflammatory process. Immunological abnormalities may be involved in the pathophysiology of depression.

Less evidence concerning the association between ambient temperature and mortality is available in developing countries/regions, especially inland areas of China, and few previous studies have compared the predictive ability of different temperature indictors (minimum, mean, and maximum temperature) on mortality. We assessed the effects of temperature on daily mortality from 2003 to 2010 in Jiang’an District of Wuhan, the largest city in central China. Quasi-Poisson generalized linear models combined with both non-threshold and double-threshold distributed lag non-linear models (DLNM) were used to examine the associations between different temperature indictors and cause-specific mortality. We found a U-shaped relationship between temperature and mortality in Wuhan. Double-threshold DLNM with mean temperature performed best in predicting temperature-mortality relationship. Cold effect was delayed, whereas hot effect was acute, both of which lasted for several days. For cold effects over lag 0–21 days, a 1 °C decrease in mean temperature below the cold thresholds was associated with a 2.39% (95% CI: 1.71, 3.08) increase in non-accidental mortality, 3.65% (95% CI: 2.62, 4.69) increase in cardiovascular mortality, 3.87% (95% CI: 1.57, 6.22) increase in respiratory mortality, 3.13% (95% CI: 1.88, 4.38) increase in stroke mortality, and 21.57% (95% CI: 12.59, 31.26) increase in ischemic heart disease (IHD) mortality. For hot effects over lag 0–7 days, a 1 °C increase in mean temperature above the hot thresholds was associated with a 25.18% (95% CI: 18.74, 31.96) increase in non-accidental mortality, 34.10% (95% CI: 25.63, 43.16) increase in cardiovascular mortality, 24.27% (95% CI: 7.55, 43.59) increase in respiratory mortality, 59.1% (95% CI: 41.81, 78.5) increase in stroke mortality, and 17.00% (95% CI: 7.91, 26.87) increase in IHD mortality. This study suggested that both low and high temperature were associated with increased mortality in Wuhan, and that mean temperature had better predictive ability than minimum and maximum temperature in the association between temperature and mortality.

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